How to filter a CSV file?

Filtering CSV files is an essential skill for data analysts, marketers, and anyone working with CSV datasets.

Whether you're cleaning web-scraped data or organizing customer information, filtering CSV files with a NoCode tool will save you time and improve your productivity.

Step-by-Step Guide to Filter CSV Files

Step 1: Load Your CSV File

The first step is to load your CSV file into Datablist. Datablist is a powerful free NoCode tool that revolutionizes the way users handle CSV data filtering and manipulation.

Create a new collection ("+" button in the left sidebar) and then click "Import CSV" to load your file.

Step 2: Apply filters

Datablist offers two ways to filter your data:

• Property filtering - Define filter criteria on one or several properties
• Full-text search - Will match any rows in your CSV that contain the keyword

Property Filtering

Once the CSV file is loaded, add filters by clicking on a property header.

Or just open the "Filtering" tool.

This opens the "Filtering" modal. Define your filter operators to select or exclude specific data.

List of filter operators for Text:

• is - Insensitive equal comparison. Leading and trailing spaces are not removed.
  • HeLLo and hello match (case insensitive)
  • "   john  " (notice the spaces) and john don't match
• is not - Opposite of "is".
• contains" - Insensitive text contains.
  • The value john@GMAIL.com with the "contains" filter gmail matches
• does not contain - Opposite of "contains".
• startswith - Insensitive text starts with
  • The value +3302934092309 with the "startswith" filter +33 matches
  • The value JOHN doe with the "startswith" filter john matches
• endswith - Insentivice text ends with
  • The value john@GMAIL.com with the "endswith" filter gmail.com matches
• in - Return items that match at least one of the comma-separated values. The comparison is case-insensitive.
  • If the "in" filter is "France, Italy, Germany, USA". An item with the value "italy" matches.
• not in - Return items with values that match none of the comma-separated values. The comparison is case-insensitive.
  • If the "not in** filter is "France, Italy, Germany, USA". An the item with the value "belgium" matches.
• is empty - Match on empty or only spaces text values
  • "    " (spaces) match
  • "" match
• is not empty - Opposite of "is empty".
• regexp - Insensitive Regex matching. See below.

List of filter operators for DateTime:

• is before - Compare the DateTime value with an absolute date and time.
• is before - relative - Check Relative datetime filtering
• is after - Compare the DateTime value with an absolute date and time.
• is after - relative - Check Relative datetime filtering
• is empty - Empty DateTime value
• is not empty - Opposite of is empty

List of filter operators for Numbers:

• = - Equal to
• ≠ - Not Equal to
• < - Less than (strict) - Equal numbers don't match
• > - Greater than (strict) - Equal numbers don't match
• ≤ - Less than or equal to
• ≥ - Greater than or equal to
• is empty - Empty cell. 0 doesn't match.
• is not empty - Opposite of is empty

You can combine multiple filter criterias using "AND" and "OR" operators. Read more about combining multiple filter criterias.

Full-text search

Filtering your items using full-text search is simple. Datablist performs a full-text search on all of your item property values in seconds.

The search input is located in the collection header. A fast way to start a search is using the keyboard shortcut Ctrl + f.

Step 4: Save & export filtered CSV data

Once your CSV file is filtered, click the "Export" button to generate a new CSV file with your cleaned and filtered data.

FAQ

What is a CSV file?

CSV (Comma Separated Value) files store structured data in text files, with each line representing a data record and fields separated by commas, semicolons, or tabs. They are widely used for transferring data between applications due to their simplicity. However, because the CSV format isn't standardized, encoding, delimiters, and escaping rules can vary. Most applications offer different options for reading CSV files. More about CSV files.

How much does it cost to filter a CSV file?

Datablist provides filtering features for free. Some advanced filtering operators such as RegEx, In, Not-In filterings, require a paid plan. See pricing.

Why Filter CSV Files?

CSV (Comma-Separated Values) files are widely used for storing and transferring data. However, raw CSV files often contain irrelevant or messy data. Filtering allows you to:

• Remove duplicate entries
• Extract specific information
• Clean and normalize data
• Prepare datasets for analysis